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Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.
In 2012, the head of AP Grading, Trevor Packer, stated that the reason for the low percentages of 5s is that "AP World History is a college-level course, & many sophomores aren't yet writing at that level." 10.44 percent of all seniors who took the exam in 2012 received a 5, while just 6.62 percent of sophomores received a 5. [23]
The field of information ethics has a relatively short but progressive history having been recognized in the United States for nearly 20 years. [6] The origins of the field are in librarianship though it has now expanded to the consideration of ethical issues in other domains including computer science, the internet, media, journalism ...
The AP U.S. History course is designed to provide the same level of content and instruction that students would face in a freshman-level college survey class. It generally uses a college-level textbook as the foundation for the course and covers nine periods of U.S. history, spanning from the pre-Columbian era to the present day.
The Principles for a Data Economy – Data Rights and Transactions is a transatlantic legal project carried out jointly by the American Law Institute (ALI) and the European Law Institute (ELI). [1] The Principles for a Data Economy deals with a range of different legal questions that arise in the data economy. [2]
The Five Safes is a framework for helping make decisions about making effective use of data which is confidential or sensitive. It is mainly used to describe or design research access to statistical data held by government and health agencies, and by data archives such as the UK Data Service.
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The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [1] This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation.